Help & Onboarding
A step-by-step guide for new team members.
Quick start
Add an agent
Save the agent's name, company or project, and phone number. The number is normalized to E.164 automatically.
Create a scenario
Choose Scripted (fixed caller lines) or Goal-based (AI simulated caller). Pick a language and define expected outcomes.
Build a suite
Group related scenarios into a test suite. Optional: schedule it to run every morning.
Run the suite
Click Run suite. Up to 3 calls run at once; the rest queue. Watch live progress on the run page.
Review results
Check pass/fail, score breakdown, transcript, recording, and retry failed tests only.
How the platform works
Vocalyze calls your production or staging Voice AI agents over the real telephone network using Twilio. During each call the platform acts as the caller: it either reads the exact lines you wrote (Scripted) or lets a simulated caller improvise within a goal you described (Goal-based). The agent's replies are transcribed, the audio is recorded, and a second pass evaluates the transcript against expected outcomes and any rubric criteria. The result is a pass/fail status, a weighted score, a written summary, and a list of specific issues.
Screen-by-screen tour
Dashboard
Your quality command centre.
- See pass rate and average score trends over the last 7, 30, or 90 days.
- Compare agent and suite scorecards: runs, pass rate, average score, p95 latency, and top recurring issues.
- The Regressions panel flags scenarios whose latest run failed after passing before, or whose score dropped by 2 or more points.
Voice Agents
Manage the AI voice agents you test.
- Add each agent's name, company or project, phone number, and environment (Production or Staging).
- Phone numbers are accepted in any local format — e.g. (650) 418-2279 — and are normalized to E.164 behind the scenes.
- You need at least one valid agent before any test can place a call.
Scenarios
Define what the test call should say and expect.
- Scripted mode: provide exact caller lines that will be read to the agent in order.
- Goal-based mode: give the simulated caller a goal prompt (e.g. 'Ask about an unexpected charge and request an explanation') and it improvises replies.
- Pick the spoken language (BCP-47). The call will use a matching Polly voice and recognition locale.
- Add expected outcomes, tags for filtering, and an optional rubric for weighted scoring.
Test Suites
Group scenarios and run them together.
- Create a suite with a name, description, and the scenarios you want included.
- Scenarios can belong to many suites, so you can reuse the same case across smoke, regression, and language suites.
- Enable 'Run daily' to include the suite in the morning sanity schedule.
Rubrics
Reusable, weighted scoring criteria.
- A rubric is a named set of criteria, each with a weight and a type.
- llm criteria are judged by the model from the transcript (task success, correctness, tone, information collected).
- latency criteria pass or fail against a threshold you set, computed from the captured call data.
- outcome criteria check for a literal expected outcome string.
Test Results
History and drill-down for every run.
- List every execution with status, score, pass/fail, agent, scenario, and run date.
- Open an execution to see the full transcript, recording player, score breakdown by criterion, and a per-turn latency view.
- For non-English calls, toggle the transcript between Original, English, and Both.
Setting up a test suite
- 1
Make sure you have a voice agent
Go to Voice Agents and add at least one agent with a reachable phone number. The call cannot start without it.
- 2
Create the scenarios you want to test
In Scenarios, click New scenario. Choose the conversation mode: • Scripted — best for deterministic regression checks. Write each caller line exactly as it should be spoken. The platform will read the lines one by one. • Goal-based — best for realistic, open-ended conversations. Describe the caller's goal and personality in the AI scenario prompt; the simulated caller will improvise replies based on what the agent says. Pick a language, add tags for filtering, and write Expected Outcomes in plain language (e.g. "Issue should be resolved", "AI should verify the account"). These outcomes are checked during evaluation.
- 3
(Optional) Create a rubric for weighted scoring
Go to Rubrics and click New rubric. Give it a name and add criteria: • llm — the model reads the transcript and scores the criterion 0-100. Use it for subjective quality checks like "Agent asked for all required details" or "Tone was polite and professional". • latency — automatic pass/fail against a threshold in seconds. Use it for SLA checks like "Agent answers within 3 seconds". • outcome — literal pass/fail based on whether a specific expected outcome was observed. Set weights to reflect importance. A criterion with weight 2 counts twice as much as a weight-1 criterion.
- 4
Build the suite
In Test Suites, click New suite. Enter a name and description, then select the scenarios to include. The picker shows each scenario's mode and tags so you can filter quickly. Enable Run this suite every morning as an automated sanity check if you want it included in the daily schedule.
- 5
Run the suite
Click Run suite. The platform creates a suite run and queues one execution per member scenario. It starts up to 3 calls in parallel; as each call finishes, the next queued scenario starts automatically. Open the suite run page to watch live progress: queued / running / passed / failed counts update in real time. Each row links to the execution detail page for that scenario.
- 6
Review results and iterate
When the run completes, review the aggregate pass rate and average score. Failed rows show why they failed. Open an execution to see: • Overall score and the weighted formula used. • A criterion-by-criterion breakdown. • The transcript with timestamps and latency chips. • The call recording (use Skip to conversation if the audio starts with ringing silence). If a few scenarios failed, use Retry failed only to re-run just those scenarios without rebuilding the queue.
- 7
Schedule daily runs and watch trends
With the daily toggle enabled, the suite runs automatically every morning via a scheduler hitting /api/public/cron/daily-tests. Return to the Dashboard to see pass-rate and score trends, latency distribution, agent scorecards, suite scorecards, and regressions.
Reading a score
Every execution is scored against a rubric if one is attached, otherwise against the expected-outcome checks. Each criterion contributes a 0-100 score multiplied by its weight. The overall score is the weighted average:
For example, if four criteria score 80, 70, 60, and 90 with equal weights of 1, the overall score is (80×1 + 70×1 + 60×1 + 90×1) / 4 = 75. The execution detail page shows the exact formula used for that run under the score badge, plus a table that lists each criterion, its score, whether it passed, and any note. A run typically passes when the overall score is 70 or higher and no high-weight criterion failed outright.
Latency explained
Latency measures the perceived response time: the moment the caller finishes speaking to the moment the AI starts its real answer. The platform estimates when the caller line finished playing and uses Twilio's partial result callback to detect when the agent's actual reply began.
If the agent says filler speech like "One moment" before answering, that filler period is captured separately and the latency chip shows how long the real answer took after it. The Dashboard's p95 latency metric and the per-suite scorecards use these values to flag slow responses.
Troubleshooting & FAQ
Glossary
- Agent
- The Voice AI being tested — configured with a name, company or project, phone number, and environment.
- Scenario
- A single test case describing what the caller will say and what the agent is expected to do.
- Suite
- A reusable group of scenarios that can be run together with one click.
- Suite run
- A single execution of every scenario in a suite, limited to 3 concurrent calls at a time.
- Execution
- One phone call and its resulting transcript, recording, and evaluation.
- Rubric
- A named set of weighted criteria used to score an execution.
- Criterion
- One rule inside a rubric (llm, latency, or outcome type).
- Regression
- A scenario that recently failed or dropped 2+ points compared with its previous run.